{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MatPlotLib 画图\n",
    "### 2003年发布0.1版，约翰霍普金斯大学使用\n",
    "由于MatPlotLib已经很老了，会有新的程序包给它做升级\n",
    "- Seaborn\n",
    "- ggplot\n",
    "- HoloViews\n",
    "- Altair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入MatPlotLib\n",
    "# import matplotlib as mpl #不常用\n",
    "import matplotlib.pyplot as plt #常用\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Solarize_Light2',\n",
       " '_classic_test_patch',\n",
       " '_mpl-gallery',\n",
       " '_mpl-gallery-nogrid',\n",
       " 'bmh',\n",
       " 'classic',\n",
       " 'dark_background',\n",
       " 'fast',\n",
       " 'fivethirtyeight',\n",
       " 'ggplot',\n",
       " 'grayscale',\n",
       " 'seaborn',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-dark',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-deep',\n",
       " 'seaborn-muted',\n",
       " 'seaborn-notebook',\n",
       " 'seaborn-paper',\n",
       " 'seaborn-pastel',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-ticks',\n",
       " 'seaborn-white',\n",
       " 'seaborn-whitegrid',\n",
       " 'tableau-colorblind10']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#设置绘图形式\n",
    "plt.style.use('classic')\n",
    "plt.style.available #列出可使用的样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 支持中文\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xc474670>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [1,2,3]\n",
    "y = [4,5,6]\n",
    "plt.plot(x,y,'r--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show() #显示图表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MatPlotLib 子图\n",
    "画两个平行的图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd500cd0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2,2,1) #（行，列，子图编号）\n",
    "plt.plot(x)\n",
    "plt.subplot(2,2,2)\n",
    "plt.plot(y)\n",
    "plt.subplot(2,2,3)\n",
    "plt.plot(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 简易线形图\n",
    "1. 画函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd575210>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure() #表示该图形\n",
    "ax = plt.axes() #表示坐标轴\n",
    "# 正弦曲线\n",
    "x = np.linspace(0,10,10000) # 0-10范围内1000个值\n",
    "y = np.sin(x)\n",
    "y1 = np.cos(x)\n",
    "plt.plot(x,y) #也可以使用ax.plot(x,y)\n",
    "plt.plot(x,y1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 图片保存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('我的图片.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. 调整线条和颜色\n",
    " 线条样式 https://matplotlib.org/stable/gallery/lines_bars_and_markers/linestyles.html?highlight=linestyle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd825530>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,color='red') #颜色支持：名称，缩写颜色代码，0-1之间的灰度值，十六进制颜色，RGB元组,HTML颜色名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd8616b0>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,linestyle='dashed') #支持线条"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd89da90>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,'-g') #支持一块使用"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 坐标轴上下限\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.5, 1.5)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlim(0,11)\n",
    "plt.ylim(-1.5,1.5)\n",
    "\n",
    "#如果想要逆序显示，就把大的放第一个参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xdf24d50>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#使用https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.axis.html?highlight=axis#matplotlib.pyplot.axis\n",
    "#plt.axis([-1,11,-1.5,2]) #传入xmin,xmax,ymin,ymax\n",
    "\n",
    "#axis能够自动收紧坐标轴\n",
    "plt.axis('tight')\n",
    "plt.plot(x,y,color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设置图形标签\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '这是y轴说明')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"这是标题\")\n",
    "plt.xlabel(\"这是x轴说明\")\n",
    "plt.ylabel(\"这是y轴说明\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xe041c10>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,label=\"第一条\") #也可以使用ax.plot(x,y)\n",
    "plt.plot(x,y1,label=\"第二条\") #也可以使用ax.plot(x,y)\n",
    "plt.legend() #显示图例"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas与MatPlotLib绘图\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                0                 1               2                    3   \\\n",
      "指标     居民人均消费支出(元)  居民人均消费支出比上年增长(%)  居民人均服务性消费支出(元)  居民人均服务性消费支出比上年增长(%)   \n",
      "2021年      24100.0              12.6         10645.0                 17.8   \n",
      "2020年      21210.0              -4.0          9037.0                 -8.6   \n",
      "2019年      21559.0               5.5          9886.0                 12.6   \n",
      "2018年      19853.0               6.2          8781.0                 12.5   \n",
      "2017年      18322.0               5.4          7803.0                  9.0   \n",
      "2016年      17111.0               6.8          7157.0                 10.8   \n",
      "2015年      15712.0               6.9          6460.0                 10.6   \n",
      "2014年      14491.0               7.5          5842.0                 11.4   \n",
      "2013年      13220.0               6.9          5246.0                  NaN   \n",
      "2012年      12054.0               8.6             NaN                  NaN   \n",
      "\n",
      "                  4                   5            6                 7   \\\n",
      "指标     居民人均食品烟酒支出(元)  居民人均食品烟酒支出比上年增长(%)  居民人均衣着支出(元)  居民人均衣着支出比上年增长(%)   \n",
      "2021年         7178.0                 NaN       1419.0               NaN   \n",
      "2020年         6397.0                 5.1       1238.0              -7.5   \n",
      "2019年         6084.0                 8.0       1338.0               3.8   \n",
      "2018年         5631.0                 4.8       1289.0               4.1   \n",
      "2017年         5374.0                 4.3       1238.0               2.9   \n",
      "2016年         5151.0                 7.0       1203.0               3.3   \n",
      "2015年         4814.0                 7.1       1164.0               5.9   \n",
      "2014年         4494.0                 8.9       1099.0               7.0   \n",
      "2013年         4127.0                 3.6       1027.0               3.6   \n",
      "2012年         3983.0                 9.6        992.0               9.9   \n",
      "\n",
      "                8                 9                 10                     11  \\\n",
      "指标     居民人均居住支出(元)  居民人均居住支出比上年增长(%)  居民人均生活用品及服务支出(元)  居民人均生活用品及服务支出比上年增长(%)   \n",
      "2021年       5641.0               NaN            1423.0                    NaN   \n",
      "2020年       5215.0               3.2            1260.0                   -1.7   \n",
      "2019年       5055.0               8.8            1281.0                    4.8   \n",
      "2018年       4647.0              13.1            1223.0                    9.1   \n",
      "2017年       4107.0               9.6            1121.0                    7.4   \n",
      "2016年       3746.0               9.6            1044.0                    9.7   \n",
      "2015年       3419.0               6.8             951.0                    6.9   \n",
      "2014年       3201.0               6.7             890.0                   10.3   \n",
      "2013年       2999.0              20.9             806.0                    8.8   \n",
      "2012年       2480.0              12.8             741.0                    9.8   \n",
      "\n",
      "                  12                  13               14  \\\n",
      "指标     居民人均交通通信支出(元)  居民人均交通通信支出比上年增长(%)  居民人均教育文化娱乐支出(元)   \n",
      "2021年         3156.0                 NaN           2599.0   \n",
      "2020年         2762.0                -3.5           2032.0   \n",
      "2019年         2862.0                 7.0           2513.0   \n",
      "2018年         2675.0                 7.1           2226.0   \n",
      "2017年         2499.0                 6.9           2086.0   \n",
      "2016年         2338.0                12.0           1915.0   \n",
      "2015年         2087.0                11.6           1723.0   \n",
      "2014年         1869.0                14.9           1536.0   \n",
      "2013年         1627.0                12.2           1398.0   \n",
      "2012年         1451.0                15.3           1262.0   \n",
      "\n",
      "                         15             16                  17  \\\n",
      "指标     居民人均教育文化娱乐支出比上年增长(%)  居民人均医疗保健支出(元)  居民人均医疗保健支出比上年增长(%)   \n",
      "2021年                   NaN         2115.0                 NaN   \n",
      "2020年                 -19.1         1843.0                -3.1   \n",
      "2019年                  12.9         1902.0                12.9   \n",
      "2018年                   6.7         1685.0                16.1   \n",
      "2017年                   8.9         1451.0                11.0   \n",
      "2016年                  11.2         1307.0                12.3   \n",
      "2015年                  12.2         1165.0                11.5   \n",
      "2014年                   9.9         1045.0                14.5   \n",
      "2013年                  10.8          912.0                 8.8   \n",
      "2012年                  11.1          838.0                12.7   \n",
      "\n",
      "                     18                     19  \n",
      "指标     居民人均其他用品及服务支出(元)  居民人均其他用品及服务支出比上年增长(%)  \n",
      "2021年             569.0                    NaN  \n",
      "2020年             462.0                  -11.8  \n",
      "2019年             524.0                    9.7  \n",
      "2018年             477.0                    6.8  \n",
      "2017年             447.0                   10.0  \n",
      "2016年             406.0                    4.4  \n",
      "2015年             389.0                    8.7  \n",
      "2014年             358.0                   10.3  \n",
      "2013年             325.0                    5.6  \n",
      "2012年             307.0                   12.9  \n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "\"None of [Index(['居民人均消费支出(元)', '居民人均食品烟酒支出(元)'], dtype='object')] are in the [columns]\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_1924\\699044148.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'年度数据.csv'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mheader\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mencoding\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'gb2312'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'居民人均消费支出(元)'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'居民人均食品烟酒支出(元)'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'2012年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2013年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2014年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2015年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2016年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2017年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2018年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2019年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2020年'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'2021年'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\PortableApps\\CommonFiles\\Python\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3462\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3463\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3464\u001b[1;33m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3466\u001b[0m         \u001b[1;31m# take() does not accept boolean indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\PortableApps\\CommonFiles\\Python\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1312\u001b[0m             \u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1314\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1315\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1316\u001b[0m         if needs_i8_conversion(ax.dtype) or isinstance(\n",
      "\u001b[1;32mD:\\PortableApps\\CommonFiles\\Python\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[1;34m(self, key, indexer, axis)\u001b[0m\n\u001b[0;32m   1372\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0muse_interval_msg\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1373\u001b[0m                     \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1374\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"None of [{key}] are in the [{axis_name}]\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1376\u001b[0m             \u001b[0mnot_found\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"None of [Index(['居民人均消费支出(元)', '居民人均食品烟酒支出(元)'], dtype='object')] are in the [columns]\""
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('年度数据.csv',index_col=0,encoding='gb2312')\n",
    "data = df.T[['居民人均消费支出(元)','居民人均食品烟酒支出(元)']]\n",
    "data = data.reindex(pd.Series(['2012年','2013年','2014年','2015年','2016年','2017年','2018年','2019年','2020年','2021年']))\n",
    "print(data)\n",
    "plt.plot(data['居民人均消费支出(元)'],label=\"人均消费\")\n",
    "plt.plot(data['居民人均食品烟酒支出(元)'],label=\"人均烟酒\")\n",
    "plt.title('人均支出')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('费用(元)')\n",
    "plt.ylim(0,30000)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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08cOSAgAAQmJJCay+vt57hLBoY6ONjTY22tho44clJbDCwkLvEcKijY02NtrYaGOjjR8unO01bpAE5KrD+cJZoLe4cBYAAOQslpTAUqmU9whh0cZGGxttbLSx0cYPS0pgtbW13iOERRsbbWy0sdHGRhs/XJPSa/ycF8hVXJMCdOCaFAAAkLNYUgAAQEgsKYHV1dV5jxAWbWy0sdHGRhsbbfywpARWUlLiPUJYtLHRxkYbG21stPHDkhJYaWmp9whh0cZGGxttbLSx0cYPSwoAAAiJJSWwlpYW7xHCoo2NNjba2Ghjo40flpTAGhoavEcIizY22thoY6ONjTZ+uJlbr3GDJCBXcTM3oAM3cwMAADmLJQUAAITEkhJYTU2N9whh0cZGGxttbLSx0cYPS0pgZWVl3iOERRsbbWy0sdHGRhs/LCmBFRcXe48QFm1stLHRxkYbG238sKQAAICQWFICa2pq8h4hLNrYaGOjjY02Ntr4YUkJrLm52XuEsGhjo42NNjba2Gjjh5u59Ro3SAJyFTdzAzpwMzcAAJCzWFIAAEBILCmBVVVVeY8QFm1stLHRxkYbG238sKQEVllZ6T1CWLSx0cZGGxttbLTxw5ISWFFRkfcIYdHGRhsbbWy0sdHGD0sKAAAIiSUlsMbGRu8RwqKNjTY22thoY6ONH5aUwNLptPcIYdHGRhsbbWy0sdHGDzdz6zVukATkKm7mBnTgZm4AACBnsaQElslkvEcIizY22thoY6ONjTZ+WFICq66u9h4hLNrYaGOjjY02Ntr44ZqUXjt0P+fNZDLKz8/v188xUNHGRhvbwbY5nK9J4Xljo033uCYlx/GXwkYbG21stLHRxkYbPywpAAAgJJaUwOrr671HCIs2NtrYaGOjjY02flhSAissLPQeISza2Ghjo42NNjba+OHC2V7jBklArjqcL5wFeosLZwEAQM7q8ZLy5ptvasqUKT167KZNm3TjjTfq4osv1qxZs9Ta2nrAA+ayVCrlPUJYtLHRxkYbG21stPHToyVl9erV+u53v6uPPvqoRx/0e9/7nkaNGqVly5bprLPO0j333HNQQ+aq2tpa7xHCoo2NNjba2Ghjo42fHl2TMmfOHE2aNEm1tbVaunRp4mM3btyoK664QsuWLdPIkSO1c+dOXXHFFXrkkUc0ZMiQfR7PNSkABgquSQE6hLkm5ZZbbtHYsWN79AE3bNigUaNGaeTIkbs/waBBOvroo/l2GQAA6JUjevKgvLy8Hn/AnTt3avjw4V1el5+fry1btvRuMvSJTCajbdu2eY/RIzt37tSgQfGv5R4oc0rM2tc2b97sPcJha6CcVUOGDOEOtIdQj5aU3hgxYoS2bt3a5XWZTKaHh0+1pCGSzpG0QtI8Se1PhnpJhZIm7Xk5JalW0vxO718nqURS6Z6XWyQ1SJrZ6TE1ksokFe95uUlSs6RpnR5TJalSUtGelxslpSVVdExaXa077rgj+2Str69XYWGhJk3aPV8qlVJtba3mz++Yr66uTiUlJSot3T1fS0uLGhoaNHNmx3w1NTUqKytTcXFx9vHNzc2aNq1jvqqqKlVWVqqoaPd8jY2NSqfTqqjYPV8mk1F1dbVuvvlmjRv3KX3wwUD5LtYnJH3sPcR+5eUdqV27/ug9Ro8MpFl3H0fbvYfohf46XzLafRYe7Pm3dp+JO58vktTU1JQ9X+rq6jRt2rQeny/z5s3rs/Mvk8noxBPHDoizasSIY5VK/U75+fld+rXz6Ncu6c+3r+ZrbGzU8uXL9fLLL2vixIl9WLZ7Pb5PSiqV0vTp0/d7TcqOHTt0+eWX6+6779YJJ5ygrVu3qry8XEuXLs3+CKgzrkmxNTU1ZZ+QB6Lj5+e/U/yuv5d0uno+64uSPt+vE3Wvt3N6aG8zEGZtd6hmPdjnTfuch99ZdbDnzcGIf1a1P282SxrDdT57HIprUvr8OymDBw/W5MmTtWDBAk2dOlVPPPGEzjzzzG4XFCTruwOjQDH/4nfW/m30ns765X6cJUlv5/TQ3mYgzNruUM16sM+bw/fHPV4LSldRn6te5w0O+AfAzz77rGbNmtXt26ZMmaIJEyZk/9mW9TgAAABLj7+TUlRU1OVHPV/60pf0pS99qdvHDh48WNddd52uu+66g58wh7W0tGR/toi9tajj5/7oijY22lg4b5LwvPES+1L6HNfQ0OA9QmC0sdHGRhsL500S2nhhSQms81Xb2BttbLSx0cbCeZOENl5YUgAAQEgsKQAAICSWlMBqamq8RwiMNjba2Ghj4bxJQhsvLCmBlZWVeY8QGG1stLHRxsJ5k4Q2XlhSAuOfAyahjY02NtpYOG+S0MYLSwoAAAiJJSWwpqYm7xECo42NNjbaWDhvktDGC0tKYM3Nzd4jBEYbG21stLFw3iShjReWlMA6/3pt7I02NtrYaGPhvElCGy8sKQAAICSWFAAAEBJLSmBVVVXeIwRGGxttbLSxcN4koY0XlpTAKisrvUcIjDY22thoY+G8SUIbLywpgRUVFXmPEBhtbLSx0cbCeZOENl5YUgAAQEgsKYE1NjZ6jxAYbWy0sdHGwnmThDZeWFICS6fT3iMElvYeILC09wCBpb0HCIvzJknae4CcxZISWEVFhfcIgdHGRhsbbSycN0lo44UlBQAAhMSSElgmk/EeITDa2Ghjo42F8yYJbbywpARWXV3tPUJgtLHRxkYbC+dNEtp4YUkJbN68ed4jBEYbG21stLFw3iShjReWlMDy8/O9RwiMNjba2Ghj4bxJQhsvLCkAACAklpTA6uvrvUcIjDY22thoY+G8SUIbLywpgRUWFnqPEFih9wCBFXoPEFih9wBhcd4kKfQeIGexpAQ2adIk7xECo42NNjbaWDhvktDGC0sKAAAIiSUlsFQq5T1CYLSx0cZGGwvnTRLaeGFJCay2ttZ7hMBoY6ONjTYWzpsktPHCkhLY/PnzvUcIjDY22thoY+G8SUIbLywpAAAgJJYUAAAQEktKYHV1dd4jBEYbG21stLFw3iShjReWlMBKSkq8RwiMNjba2Ghj4bxJQhsvLCmBlZaWeo8QGG1stLHRxsJ5k4Q2XlhSAABASCwpgbW0tHiPEBhtbLSx0cbCeZOENl5YUgJraGjwHiEw2thoY6ONhfMmCW28sKQENnPmTO8RAqONjTY22lg4b5LQxgtLCgAACIklBQAAhMSSElhNTY33CIHRxkYbG20snDdJaOOFJSWwsrIy7xECo42NNjbaWDhvktDGC0tKYMXFxd4jBEYbG21stLFw3iShjReWFAAAEBJLSmBNTU3eIwRGGxttbLSxcN4koY0XlpTAmpubvUcIjDY22thoY+G8SUIbLywpgU2bNs17hMBoY6ONjTYWzpsktPHCkgIAAEJiSQEAACGxpARWVVXlPUJgtLHRxkYbC+dNEtp4YUkJrLKy0nuEwGhjo42NNhbOmyS08cKSElhRUZH3CIHRxkYbG20snDdJaOOFJQUAAITEkhJYY2Oj9wiB0cZGGxttLJw3SWjjhSUlsHQ67T1CYGnvAQJLew8QWNp7gLA4b5KkvQfIWSwpgVVUVHiPEBhtbLSx0cbCeZOENl5YUgAAQEgsKYFlMhnvEQKjjY02NtpYOG+S0MYLS0pg1dXV3iMERhsbbWy0sXDeJKGNF5aUwObNm+c9QmC0sdHGRhsL500S2nhhSQksPz/fe4TAaGOjjY02Fs6bJLTxwpICAABCYkkJrL6+3nuEwGhjo42NNhbOmyS08cKSElhhYaH3CIEVeg8QWKH3AIEVeg8QFudNkkLvAXIWS0pgkyZN8h4hMNrYaGOjjYXzJgltvLCkAACAkFhSAkulUt4jBEYbG21stLFw3iShjReWlMBqa2u9RwiMNjba2Ghj4bxJQhsvLCmBzZ8/33uEwGhjo42NNhbOmyS08cKSAgAAQmJJAQAAIbGkBFZXV+c9QmC0sdHGRhsL500S2nhhSQmspKTEe4TAaGOjjY02Fs6bJLTxwpISWGlpqfcIgdHGRhsbbSycN0lo44UlBQAAhMSSElhLS4v3CIHRxkYbG20snDdJaOOFJSWwhoYG7xECo42NNjbaWDhvktDGC0tKYDNnzvQeITDa2Ghjo42F8yYJbbywpAAAgJBYUgAAQEgsKYHV1NR4jxAYbWy0sdHGwnmThDZeWFICKysr8x4hMNrYaGOjjYXzJgltvBzR0weuWrVKd955p1pbW/XlL39ZN9xwg/Ly8szH/+d//qduu+02DR06VJI0dOhQPfzwwwc/cQ4pLi72HiEw2thoY6ONhfMmCW289Og7KVu2bNHs2bNVUVGhxx9/XB988IGefvrpxPdZs2aNrr/+ei1fvlzLly9nQQEAAL3SoyWlqalJI0eO1Fe+8hUNGjRIV155pZ555pnE93n99dd16qmn9smQuaqpqcl7hMBoY6ONjTYWzpsktPHSoyVlw4YNXRaO448/Xu+88475+J07d2rt2rW68847ddFFF+nrX/+6Xn311YMeNtc0Nzd7jxAYbWy0sdHGwnmThDZeerSk7Nq1S8OHD8++PHToUG3dutV8/ObNm/XFL35Rt99+u37yk5+ovLxct956q7Zv337wE+eQadOmeY8QGG1stLHRxsJ5k4Q2Xnq0pBQUFHRZStra2jRokP2uhYWFuummmzR69GhJ0le/+lV9/PHHeuutt/bzmaolzZD00z3/m+n0tnpJjZ1eTkmq2uv969T123It2vefjtWo6+9haNrzfp1V7fn47Rr3fP5Ok1ZXK5PpmK++vl6NjR3zpVIpVVV1na+urq7Lt1RbWlr2+Wd/NTU1XX6HRlNTk+rqus5XVVWlVKpjvsbGRtXXd8yXyWQ0Y8aMLvPF6pfRvn++P9nrY0Sbb+9+64PPl5J0W/D59u4nSS8Gnq9O0kvB5+v857tWe+uv86Wvzj9poeL06+7Pd2GXl6L1OxR/vo2NjZo2bZomTpyo6upq9be8FStW7Nrfg95++23Nnj1bjzzyiPLy8vTCCy/o+9//vh566KFuH79u3TqlUilNnDhR0u4v+vzzz9d9992nU045pctjP/zwQ11wwQV7XmqVVHAwX88hsFnSCLW2tqqgIPasmzdv1ogRIzQwur4naYzizzpQ5pSYtT8MlDklzqr+MHCaHgrtf25PPvmkhg0b1i+fo0ffSTnppJN0zDHHaNGiRXr11VdVV1en8847z3z8xx9/rDvuuEPr1q3T1q1bdd9992nMmDE66aST+mzwXLD3Jo3OaGOjjY02Fs6bJLTx0uObud16663KZDKqra1VaWmpKioq9Nprr2nq1Kn7PHbcuHG65pprNH36dF199dX63//9X82bN0+DBw/u0+EPd5WVld4jBEYbG21stLFw3iShjZce38zt6KOP3ue3ZI4fP16LFy/u9vEXXXSRLrroooObLscVFRV5jxAYbWy0sdHGwnmThDZeuC0+AAAIiSUlsM5Xe2NvtLHRxkYbC+dNEtp4YUkJLJ1Oe48QWNp7gMDS3gMElvYeICzOmyRp7wFyFktKYBUVFd4jBEYbG21stLFw3iShjReWFAAAEBJLSmBd7xiLrmhjo42NNhbOmyS08cKSEtihuOXwwEUbG21stLFw3iShjReWlMDmzZvnPUJgtLHRxkYbC+dNEtp4YUkJLD8/33uEwGhjo42NNhbOmyS08cKSAgAAQmJJCazzr8/G3mhjo42NNhbOmyS08cKSElhhYaH3CIEVeg8QWKH3AIEVeg8QFudNkkLvAXIWS0pgkyZN8h4hMNrYaGOjjYXzJgltvLCkAACAkFhSAkulUt4jBEYbG21stLFw3iShjReWlMBqa2u9RwiMNjba2Ghj4bxJQhsvLCmBzZ8/33uEwGhjo42NNhbOmyS08cKSAgAAQmJJAQAAIbGkBFZXV+c9QmC0sdHGRhsL500S2nhhSQmspKTEe4TAaGOjjY02Fs6bJLTxwpISWGlpqfcIgdHGRhsbbSycN0lo44UlBQAAhMSSElhLS4v3CIHRxkYbG20snDdJaOOFJSWwhoYG7xECo42NNjbaWDhvktDGC0tKYDNnzvQeITDa2Ghjo42F8yYJbbywpAAAgJBYUgAAQEgsKYHV1NR4jxAYbWy0sdHGwnmThDZeWFICKysr8x4hMNrYaGOjjYXzJgltvLCkBFZcXOw9QmC0sdHGRhsL500S2nhhSQEAACGxpATW1NTkPUJgtLHRxkYbC+dNEtp4YUkJrLm52XuEwGhjo42NNhbOmyS08cKSEti0adO8RwiMNjba2Ghj4bxJQhsvLCkAACAklhQAABASS0pgVVVV3iMERhsbbWy0sXDeJKGNF5aUwCorK71HCIw2NtrYaGPhvElCGy8sKYEVFRV5jxAYbWy0sdHGwnmThDZeWFIAAEBILCmBNTY2eo8QGG1stLHRxsJ5k4Q2XlhSAkun094jBJb2HiCwtPcAgaW9BwiL8yZJ2nuAnMWSElhFRYX3CIHRxkYbG20snDdJaOOFJQUAAITEkhJYJpPxHiEw2thoY6ONhfMmCW28sKQEVl1d7T1CYLSx0cZGGwvnTRLaeGFJCWzevHneIwRGGxttbLSxcN4koY0XlpTA8vPzvUcIjDY22thoY+G8SUIbLywpAAAgJJaUwOrr671HCIw2NtrYaGPhvElCGy8sKYEVFhZ6jxBYofcAgRV6DxBYofcAYXHeJCn0HiBnsaQENmnSJO8RAqONjTY22lg4b5LQxgtLCgAACIklJbBUKuU9QmC0sdHGRhsL500S2nhhSQmstrbWe4TAaGOjjY02Fs6bJLTxwpIS2Pz5871HCIw2NtrYaGPhvElCGy8sKQAAICSWFAAAEBJLSmB1dXXeIwRGGxttbLSxcN4koY0XlpTASkpKvEcIjDY22thoY+G8SUIbLywpgZWWlnqPEBhtbLSx0cbCeZOENl5YUgAAQEgsKYG1tLR4jxAYbWy0sdHGwnmThDZeWFICa2ho8B4hMNrYaGOjjYXzJgltvLCkBDZz5kzvEQKjjY02NtpYOG+S0MYLSwoAAAiJJQUAAITEkhJYTU2N9wiB0cZGGxttLJw3SWjjhSUlsLKyMu8RAqONjTY22lg4b5LQxgtLSmDFxcXeIwRGGxttbLSxcN4koY0XlhQAABASS0pgTU1N3iMERhsbbWy0sXDeJKGNF5aUwJqbm71HCIw2NtrYaGPhvElCGy8sKYFNmzbNe4TAaGOjjY02Fs6bJLTxwpICAABCYkkBAAAhsaQEVlVV5T1CYLSx0cZGGwvnTRLaeGFJCayystJ7hMBoY6ONjTYWzpsktPHCkhJYUVGR9wiB0cZGGxttLJw3SWjjhSUFAACExJISWGNjo/cIgdHGRhsbbSycN0lo44UlJbB0Ou09QmBp7wECS3sPEFjae4CwOG+SpL0HyFksKYFVVFR4jxAYbWy0sdHGwnmThDZeWFIAAEBILCmBZTIZ7xECo42NNjbaWDhvktDGS4+WlFWrVun6669XeXm57rnnHu3atSvx8W1tbZozZ47Kysr0zW9+U6lUqk+GzTXV1dXeIwRGGxttbLSxcN4koY2X/S4pW7Zs0ezZs1VRUaHHH39cH3zwgZ5++unE91m0aJHa2tr0ox/9SNdee63mzZvXZwPnknPOOcd7hMBoY6ONjTYWzpsktPGy3yWlqalJI0eO1Fe+8hUNGjRIV155pZ555hnz8du3b9dzzz2nr33taxoyZIgmTpyoDz/8UOvXr+/TwXPBihUrvEcIjDY22thoY+G8SUIbL/tdUjZs2KBTTz01+/Lxxx+vd955x3x8a2urtm3bplNOOSX7uhNOOEHvvvvuwU0KAAByyhH7e8CuXbs0fPjw7MtDhw7V1q1bzcfv3LlT+fn5OuKIjg+dn5+vLVu2mB+/w+8lbd7/1K52fx2///3vtXlz/87a3Nys995774Dfv6P5QOj6/p7/7emszZIOvM2B6+2cHtrbDIRZ2x2qWQ/2eTOQmvburDrY8+ZgxD+r2p83u+fs77N/oGjvsL/rVA/GfpeUgoICrVu3LvtyW1ubBg2yvwFTUFCgTCaj7du3ZxeVTCZjvk9bW1unl07v4dj+Tj/90Mw6ZsyYPvgoA6dr72btizYHKnrTzm2iz9rZoZg1t/5O9eas6pvz5mBE7trRxr9TLG1tbV2+mdGX9rukjB8/Xo8++qh27dqlvLw8rV69OvEXUR155JEaN26cVq1apQkTJmjHjh1qaWnRVVdd1e3jjznmGD322GMaOnSo8vLyDvwrAQAAh8yuXbvU1tamY445pt8+x36XlJNOOknHHHOMFi1apHPOOUd1dXU677zzEt/nwgsv1KJFi1RZWalf/vKXOuqoo1RcXNztYwcNGqTjjjvuwKYHAABu+us7KO3yVqxYsd8fJv3f//2f7r//fq1du1alpaWaMmWKXn/9dS1cuFCLFy/u9n2WL1+uxsZGHXvssbrhhht04okn9vnwAADg8NWjJQUAAOBQ67Pb4r/55puaMmVK9uVMJqO5c+dq8uTJuuCCC/Tggw9m35Z0R9p3331XN9xwgy6++GL90z/9k7Zt25Z923/913/pqquu0uWXX66lS5f21ej9bu82nf3sZz/T9OnTsy9v2rRJN954oy6++GLNmjVLra2t2bcl3fn3Jz/5iS6//HJdeeWV+vnPf95vX0tfs9ps2rRJl1xyidasWZN9Xa4/b9ra2jR79mxdeumluvzyy/XII49k35ZLz5unn35al112mc4991zNmDFDmzZtkmR/LTt27NDChQt18cUXa+rUqXrjjTeybzvQbhF112Xnzp1atGiRzj//fE2ePFn//M//rB07dkjKnS6S/Zxp99JLL3W5bjKXzpqkNm1tbbrmmmv0/PPPZ193qJ83fbKkrF69Wt/97nf10UcfZV93//33Ky8vT48++qjuuusuLVu2TM3NzZLsO9Lu2LFDs2fP1l/8xV/oxz/+sUaNGqUlS5ZIkt577z3deuutuvHGG/XII49o5cqV+s1vftMX4/er7tq0e//993X33Xd3ed33vvc9jRo1SsuWLdNZZ52le+65R1LynX9feeUV1dXVacGCBXrggQf06KOPdvkXWVEltbnjjjs0adIknXbaadnX5frz5tFHH9Wf/umfatmyZfr+97+vZcuW6bXXXpOUO8+bNWvW6Ic//KHmzp2rJ554QkOGDNEDDzyQ+LUsWbJEr7/+upYsWaLq6mrdeuut2f9QH0i3iKwujz/+uN555x09+OCDevDBB/Xiiy/qF7/4haTc6CLZbdpt3bpVt912m3bu3Jl9Xa6cNftrU1dXp5NPPll/9Vd/lX3doX7e9MmS8thjj6mysrLL68444wz9wz/8gwoLC3XyySfrk5/8pFKpVOIdaVevXq10Oq2rr75aeXl5qqioyN7d9rnnntOECRM0YcIEfeITn9Bll12W/csWWXdtpN33k5k3b57++q//Ovu6jRs36pVXXtHUqVM1ePBgXXDBBXrppZe0bdu2xDv//uIXv9C5556rsWPHavjw4Zo8efKAuHuk1eapp57SunXrdP3112dfx/NGeuONNzRhwgRJ0nHHHaexY8fq/fffz6nnzeDBgzVnzhydfvrpGj58uM466yytX78+8Wv5+c9/rr/927/V8OHDNW7cOI0ZM0avvfbaAXeLyOoyZswYVVVVafTo0Tr++ON1xhlnZL8rkAtdJLtNu4ULF+qzn/1s9uVcOmuS2vzmN7/RihUr9O1vf7vL+xzq502fLCm33HKLxo4d2+V1X/7ylzV06FBJu//j+9Zbb+nTn/504h1pN2zYoHHjxmXvr1JQUKAtW7boj3/8o9avX7/PnW8Hwl1su2sj7f5/xccdd5wmTZqUfd2GDRs0atQojRw5UtLuf/l09NFHK5VKJd75d/369V2+4zCQ22zatEn33nuvhg8frn/8x3/Uww8/rG3btvG8kXTqqafqySef1NatW7Vq1ars0pJLz5uTTz5Zn/rUp7Ivr1y5Up/5zGcSv5YNGzZ0eVvn582BdIvI6vKFL3wh+68n29ra9PLLL6ukpERSbnSR7DaS9Mwzz2jDhg265pprsm/PpbPGapPJZHT77bersLBQt99+u37wgx9kb+J6qJ83fbKk7O/+JnfffbfOPfdcnXDCCYl3pN25c+c+/5zpyCOP1NatW3t959soumvzxhtv6Gc/+5lmzJjR5fXdff3tbZK+/u7eZt3hN5Lu2vzbv/2b8vLydPHFF+u8887TihUrtGDBAp43ki666CKtXbtW1dXVmjt3ri699FIde+yxOfe8abdy5Uq1tLTosssuS/xa9u6T9LzpSbfoOnfp7KGHHtJJJ52kM888U1LudZG6ttm4caN+8IMfaPbs2Ro8eHD2Mbl21rTr3ObHP/6xPvjgA1100UU6//zz9frrr6uqqkrSoX/e7Pc+KQfriSee0Ntvv6377rtPUvIdaf/kT/5kn8Hb31ZQUNDlbfu7821U27Zt0/z583XTTTft8wc6YsSIxK/fuvNvd206/6UbSF5++WVdffXVmjx5siTp2GOP1Xe+8x3deOONOf28kaTbbrtN1dXVOvPMM7Vt2zbNmDFDxx9/vE477bSce96sX79eCxYs0MyZMzV8+PDEr6X9bQUFBZJ2tznqqKMO+O9bZHt3abdy5Ur9x3/8h+rq6rKvy6UuUtc2w4YN080336ypU6eqqKioy4WxufjfqL2fNy+//LK++tWv6tJLL5UkFRcX6/LLL9fGjRsP+fOmXwv++te/1r/+679q7ty5GjZsmKSud6SVlL0jbVFRkYqLi/X2229nb5W/bt067dixQwUFBRo/fnz2wltJ+73zbVRr1qzR+vXrNWfOHJWXl+vmm2/Wb3/7W5WXl+vEE0/Uxx9/rD/84Q+Sdl/Q9e6772r06NEaP368Vq1alb0iuvPX312b0aNHH/ovrg8cddRROuGEE7IvH3nkkRo2bFjOP2+k3b9bZdy4cZKkIUOG6NRTT9WqVaty7nmzdetWVVdX65JLLlFpaamk5K9l77f99re/VVFR0QF3i6q7LpL01ltv6bbbbtPNN9+sUaNGZV+fK12kfdts2LBBLS0tuvfee1VeXq5vfOMb2rhxo8rLy9Xa2ppTZ013z5vuzuG8vDwNGzbskD9v+m1JWbNmjebMmaPq6up9frbefkfaV155Rffdd1/2jrQFBQWaOHGiampq9Nprr+muu+7Sueeeq8GDB+vzn/+8NmzYoCVLlujXv/61lixZst8730b06U9/Wk899ZSWL1+u5cuXa+7cuTrjjDO0fPlyDR48WJMnT9aCBQu0atUqLVy4UGeeeaZGjhzZ5c6/r776apc7/55zzjn67//+bz311FN6/vnn9dOf/lR/8zd/4/yVHpizzz5b//7v/64//vGP2rZtm5YuXZq9qC2XnzfS7t8XsnTpUq1bt04rV67UM888o3HjxuXU82b79u3ZM+Xaa6/Nvj7pa7nwwgv14IMP6oUXXtCjjz6q999/XxMnTjzgbhFZXdavX68bb7xRX//617MXXbfLhS5S921Gjx6tp59+OnsO33fffTruuOO0fPlyjRo1KmfOGut585d/+ZdasWKFtmzZoh07dujhhx/W6aefrqOOOuqQP2/67GZuqVRK06dPz/7b8Jtvvlm/+tWvst8SkqTy8vLsBUrWHWnb2tr04IMP6qWXXtL48eP1jW98I3sB7h/+8Afdf//9eu+993Teeefpiiuu6IvR+93ebTp75ZVX9NBDD+muu+6StHtrX7JkiZ5//nn9+Z//uf7+7/8+eyFSd3f+bf+W9tq1a7V48WKl02lddtll4f9j027vNtu3b9fixYu1YsUKffTRRxo/frxmzZqVfR7l8vNm7dq1qq2t1dtvv61BgwbpvPPO07e+9S0NGjQoZ543v/rVrzR79mwVFBRkv4ajjz5aixcvTvxann32WT3++OPKz8/X3/3d32V/TceBdovG6vLZz35Wjz/+uAoLC7OPPfvss7PXwx3uXaTk50y77s7oXDhrrDYPPPCAli5dmr1Q/5Of/KRmzZql448/XtKhfd5wx1kAABDSwLiqBwAA5ByWFAAAEBJLCgAACIklBQAAhMSSAgAAQmJJAQAAIbGkAACAkFhSAABASP8P4zQAwHGfrhgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['居民人均消费支出(元)'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
